Teaching Visualization-first for Novices to Understand Programming

Hu, Minjie; Assadi, Tony; Mahroeian, Hamidreza

doi:10.1109/tale52509.2021.9678922

Cited by 3 publications

(1 citation statement)

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“…When supporting learners’ self-regulated learning aspects, their cognitive load needs to be considered because one of the learning performance issues might be caused by learners’ cognitive overload during the problem-solving process in computer programing learning (Stachel et al, 2013; Yousoof et al, 2006). Learners’ cognitive overload could happen in computer programing due to the intrinsic complexity of tasks because programing requires the constant computational-abstraction process, accurate and repetitive interpretation of computer codes (Hu, 2005; Paas & Van Merriënboer, 1994).…”

Section: Literature Reviewmentioning

confidence: 99%

The Effects of Self-Regulated Learning Support on Learners’ Task Performance and Cognitive Load in Computer Programing

Shin

Song

2022

Journal of Educational Computing Research

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This study explores the effect of self-regulated learning support on learners’ cognitive load and problem-solving performance, considering cases from well-structured to ill-structured tasks in a computer programing course. Sixty-seven undergraduate students in a computer programing fundamentals course were randomly assigned into one of two groups: (1) experimental group ( N = 34; received self-regulated learning support) and (2) control group ( N = 33). Participants in both groups were asked to solve programing problems using Python over 3 weeks, and their cognitive load levels were measured after each week. The results showed that novice learners’ self-regulated learning skills can be influenced by learning support, which contributes to solving complex problems. The results also suggest that, given the sequence of tasks (i.e., basic and advanced well-structured and ill-structured problems), self-regulated learning support may require time to be effective. The germane load of the experimental group was higher for well-structured problems than that of the control group. Using logistic regression, the two groups were differentiated through different variables measured in this study, which showed a high predictive explanatory power. The results provide implications for designing self-regulated learning support for programing courses, using problem-based learning in association with problem-solving skills, self-regulated learning skills, and cognitive load management.

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Section: Literature Reviewmentioning

confidence: 99%